Redistributed Manufacturing and the Impact of Big Data: A Consumer Goods Perspective

Abstract

Digitalization and the growth of big data promise greater customization as well as change in how manufacturing is distributed. Yet, challenges arise in applying these new approaches in consumer goods industries that often emphasize mass production and extended supply chains. We build a conceptual framework to explore whether big data combined with new manufacturing technologies can facilitate redistributed manufacturing (RDM). Through analysis of 24 consumer goods industry cases using primary and secondary data, we investigated evolving manufacturing configurations, their underlying drivers, the role of big data applications, and their impact on the redistribution of manufacturing. We find some applications of RDM concepts, although in other cases existing manufacturing configurations are leveraged for high volume consumer goods products through big data analytics and market segmentation. The analysis indicates that the framework put forward in the paper has broader value in organizing thinking about emerging interrelationships between big data and manufacturing.     

Understanding the emergence of redistributed manufacturing: an ambidexterity perspective

Abstract

This paper extends operations strategy theory on efficiency and flexibility trade-offs to the emergent phenomenon of redistributed manufacturing (RDM). The study adopts a multiple-case design including five small and five large pharmaceutical firms. We propose that organizations can gain the efficiency benefits of centralized manufacturing and the flexibility advantages of RDM by building an ambidexterity capability. To build such a capability, large firms can structurally partition their manufacturing and supply management functions, with one sub-unit managing centralized production and the other RDM. Smaller enterprises can build an ambidexterity capability by creating the right organizational context, where multi-skilled workers switch between efficient and flexible tasks. This paper contributes to theory by explaining the emergence of RDM using an organizational ambidexterity lens, laying the groundwork for new theory development in the field. We provide managers with a practical example of how to build an ambidexterity capability to realize flexibility and efficiency advantages.     

Redistributing food manufacturing: models for the creation and operation of responsive and agile production networks

Abstract

The food industry is a mature industry where its profit margins are thin and its R&D failure rate for new products is substantial. Both facts indicate that decent return on development investment cannot be provided and that the food industry cannot still rely on its traditional way of thinking and innovating. New product development cycles should involve not only the product itself but also the entire manufacturing and distribution network. Hence, collaborative manufacturing and servitization models are key elements for the rapid transformation of the new food industry. Moreover, recent developments in technology have the potential to shift manufacturing production away from large scale manufacturing plants to a network of distributed, smaller scale localized and customizable manufacturing facilities. Such a network is the crucial enabler for the on-demand manufacture of new or even, existing food products to rapidly respond to the consumers´ demands.     

A vision of re-distributed manufacturing for the UK’s consumer goods industry

Abstract

The linear production of consumer goods is characterised by mass manufacture, multinational enterprises and globally dispersed supply chains. Redistributed manufacture (RDM) is an emerging topic, which seeks to enable a transition of the current linear model of production and consumption, by taking advantage of new technologies. This paper aims to explore the challenges, opportunities and further research questions to set a vision of Redistributed manufacturing for the UK’s consumer goods industry. To set this vision, a literature survey was conducted followed by a qualitative enquiry where PESTLE¹ aspects of RDM were analysed. This analysis was interpreted through a roadmap. As a result of this roadmap, four RDM characteristics (i.e. customisation, use of digital technologies, local production and the development of new business models) were identified. These characteristics helped to set the future vision of RDM in the UK’s consumer goods sector.     

The implementation of digital technologies for operations management: a case study for manufacturing apps

Abstract

Manufacturing applications address business to business (B2B) with highly customised applications developed for specific requirements, offering highly specialised solution-oriented and service-based software components, systems, and digital tools that aim at a fast and accurate decision-making support system. The purpose of this paper is to describe the implementation of digital technologies for operations management using manufacturing or engineering apps (eApps), for product design and manufacturing processes. In particular, starting from the specific needs of two companies from mature European industries as automotive and food, this work depicts how this kind of solutions can support companies and improve their operations. In particular, related benefits and challenges faced for the full implementation of the developed tools are highlighted. Moreover a business model to exploit the manufacturing apps is also proposed. The business model proposed for the exploitation of the eApps supports the commercialisation of all the revenue streams offered by this rapidly growing sector taking into account the specific needs of the concerned stakeholders through a diversified value proposition.     

Do makerspaces represent scalable production models of community-based redistributed manufacturing?

Abstract

This research explores the development of local community-based ‘makerspaces’ as potential scalable forms of redistributed manufacturing (RDM). Makerspaces are rapidly emerging in post-industrial economies and have been identified as a catalyst of local regeneration in urban areas. However, their role in local production systems is limited. There is a gap in the literature, with respect to the evolution of makerspaces and their productive contribution. The purpose of this paper therefore is to identify, classify and examine the different types of makerspaces. Our focus is on the implementation characteristics that enable industrial production activity to take place. First, we used Leximancer (to identify from the literature) three types of makerspace. Second, we then identify five RDM implementation characteristics. The characteristics were integrated together to form the RDM-makerspace implementation model. Third, case studies were purposively selected to test and advance this model. They were subsequently classified as a Type 1 (educational), Type 2 (design) or Type 3 (production) makerspace. Only one of the case studies was classified as a fully evolved Type 3 production space. The findings concur with the literature that makerspaces tend to be primarily Type 1 or Type 2. Finally, the contribution to local production theory is emphasized.     

Cloud platforms for remote monitoring system: a comparative case study

Abstract

Currently, industrial companies are increasingly introducing services to extend their tangible products. Remote monitoring solutions are one of the most implemented services by machine builders to manage their relationship with customers and also improve their business performance in the digital manufacturing era. However, the conventional method of remote monitoring cannot fulfill distributed business environments. Therefore, new solutions are needed to enable remote connection in manufacturing. By reviewing recent literature and proposing new features for software which can be used for remote service and operations, this research paper introduces a remote monitoring system connecting into a central cloud-based system with edge computing network architecture, namely Cloud-based Remote Monitoring (CloudRM). This proposed CloudRM also has been implemented in two different case companies for analysis and evaluation from a value proposition and technical implementation point of view. It shows significant improvement in production management and measurement by using CloudRM.     

Adaptive agent-based manufacturing control and its application to flow shop routing control

The manufacturing industry is currently facing unprecedented challenges from changes and disturbances. The sources of these changes and disturbances are of different scope and magnitude. They can be of a commercial nature, or linked to fast product development and design, or purely operational (e.g. rush order, machine breakdown, material shortage etc.). In order to meet these requirements it is increasingly important that a production operation be flexible and is able to adapt to new and more suitable ways of operating. This paper focuses on a new strategy for enabling manufacturing control systems to adapt to changing conditions both in terms of product variation and production system upgrades. The approach proposed is based on two key concepts: (1) An autonomous and distributed approach to manufacturing control based on multi-agent methods in which so called operational agents represent the key physical and logical elements in the production environment to be controlled – for example, products and machines and the control strategies that drive them and (2) An adaptation mechanism based around the evolutionary concept of replicator dynamics which updates the behaviour of newly formed operational agents based on historical performance records in order to be better suited to the production environment. An application of this approach for route selection of similar products in manufacturing flow shops is developed and is illustrated in this paper using an example based on the control of an automobile paint shop.     

The workflow system and its applications

Recent information technological advances have led to the workflow system that provides an effective technical solution for productivity improvement and business process reengineering. Workflow is a network of activities, also commonly known as a business process, defined for a specific business objective. The fundamental principle of workflow technology is the separation of business process from (software) applications and data. This implies a flexible, adaptable system that can support dynamic business changes. This flexibility, however, is not built upon complexity. Instead, the system should be easily modified for a new business environment. On the other hand, a good workflow system facilitates individual tasks, and collectively the entire business process by providing accurate inputs (data, forms tools) and effective routing control. Workflow technology has a wide range of applications and, when appropriately implemented, can increase productivity, reduce operating costs, improve response to customer requests and shorten the business process cycle. A great opportunity for a company is in evidence to advance its competition edge to a new level through implementation of workflow technology in the next few years. This paper discusses workflow environments, system components, architecture, integrated applications for external program execution, and future trends.     

Cloud manufacturing system for sheet metal processing

Abstract

Cloud computing is changing the way industries and enterprises run their businesses. Cloud manufacturing is emerging as an approach to transform the traditional manufacturing business model, while helping the manufacturer to align production efficiency with its business strategy, and creating intelligent factory networks that enable collaboration across the whole enterprise. Many production planning and control (PPC) problems are essentially optimisation problems, where the objective is to develop a plan that meets the demand at minimum cost or maximum profit. Because the underlying optimisation problem will vary in the different business and operation phases, it is important to think about optimisation in a dynamic mechanism and in a number of interlinked sub-problems at the same time. Cloud manufacturing has the potential to offer decision support as a service and medium of communication in PPC. To solve these problems and produce collaboration across the supply chain, this paper provides an overview of the state of the art in cloud manufacturing and presents a model of cloud-based production planning and production system for sheet metal processing.     

Sensitivity Analysis for Critical Control Points Determination and Uncertainty Analysis to Link FSO and Process Criteria: Application to Listeria monocytogenes in Soft Cheese Made from Pasteurized Milk

Microbiological food safety is an important economic and health issue in the context of globalization and presents food business operators with new challenges in providing safe foods. The hazard analysis and critical control point approach involve identifying the main steps in food processing and the physical and chemical parameters that have an impact on the safety of foods. In the risk‐based approach, as defined in the Codex Alimentarius, controlling these parameters in such a way that the final products meet a food safety objective (FSO), fixed by the competent authorities, is a big challenge and of great interest to the food business operators. Process risk models, issued from the quantitative microbiological risk assessment framework, provide useful tools in this respect. We propose a methodology, called multivariate factor mapping (MFM), for establishing a link between process parameters and compliance with a FSO. For a stochastic and dynamic process risk model of in soft cheese made from pasteurized milk with many uncertain inputs, multivariate sensitivity analysis and MFM are combined to (i) identify the critical control points (CCPs) for throughout the food chain and (ii) compute the critical limits of the most influential process parameters, located at the CCPs, with regard to the specific process implemented in the model. Due to certain forms of interaction among parameters, the results show some new possibilities for the management of microbiological hazards when a FSO is specified.     

When Evolution Works Against the Future: Disgust's Contributions to the Acceptance of New Food Technologies

New food technologies have a high potential to transform the current resource‐consuming food system to a more efficient and sustainable one, but public acceptance of new food technologies is rather low. Such an avoidance might be maintained by a deeply preserved risk avoidance system called disgust. In an online survey, participants (N = 313) received information about a variety of new food technology applications (i.e., genetically modified meat/fish, edible nanotechnology coating film, nanotechnology food box, artificial meat/milk, and a synthetic food additive). Every new food technology application was rated according to the respondent's willingness to eat (WTE) it (i.e., acceptance), risk, benefit, and disgust perceptions. Furthermore, food disgust sensitivity was measured using the Food Disgust Scale. Overall, the WTE both gene‐technology applications and meat coated with an edible nanotechnology film were low and disgust responses toward all three applications were high. In full mediation models, food disgust sensitivity predicted the disgust response toward each new food technology application, which in turn influenced WTE them. Effects of disgust responses on the WTE a synthetic food additive were highest for and lowest for the edible nanotechnology coating film compared to the other technologies. Results indicate that direct disgust responses influence acceptance and risk and benefit perceptions of new food technologies. Beyond the discussion of this study, implications for future research and strategies to increase acceptance of new food technologies are discussed.     

Towards an adapted lean system – a push-pull manufacturing strategy

Abstract

The direct transplantation or imitation of lean production has led to difficulties of applying a number of lean principles and practices. Thus diffusion of one of the main lean principles, just in time production, which refers to producing only “what is really needed, when it is needed, and in the amount needed”, seems to be limited. To date, some of the these companies produce more than their customers really need. This method of production enables them not only to amortize the high changeover costs over a large number of products, but also to benefit from commercial opportunities. However these companies are exposed to financial losses related to storage costs and risks of non-sale. To provide decision elements for determining the best production strategy, we have developed a model for calculating the optimal quantity to be produced. Moreover, we suggest using a fuzzy aggregation system to optimise the consideration of the risk of non-sale. This new approach defines the limits to not be exceed by taking into consideration the drawbacks linked to the risks of non-sale.     

A chain game for distributed trading and negotiation

This position paper introduces a simulation gaming environment for enacting a production network. The environment aims to be an integrative laboratory for investigating supply networks, as well as being a versatile training tool. The primary focus is on food production networks. The environment enables a number of teams of participants, each representing one actor in a food chain, to conduct business together. The teams can have the role of auction, co-operation, wholesaler, factory, retail chain, and retail outlet. Producers and consumers are either enacted or simulated. The game leaders freely determine the products and production methods in each run of the game. The gaming environment takes performance, process and institutional aspects of chains into account. It is particularly suited for investigating issues of sustainability and trust. Currently the gaming environment is under development. The paper presents version 1B. This version can be found at http://www.chaingame.org. It runs on the Web, enabling to model distributed chains.     

Knowledge management for food supply chain synergies – a maturity level analysis of SME companies

Abstract

Despite the considerable number of papers addressing knowledge management (KM) aspects in supply chains, many research issues in the area are still neglected. One of the main research gaps in this field concerns the maturity level of KM practices adoption by small and medium enterprises (SMEs). This paper addresses this research gap by developing a framework to support the analysis of the maturity level of KM adoption in an SME context. The framework is applied in a multiple case study developed to investigate the extent to which SMEs operating in the food sector are deploying KM practices to support more sustainable initiatives. By relating KM maturity levels, perspectives and processes to sustainable practices concerning food waste and by-product synergies, the paper makes an original contribution to advance theory and practice in the area. The paper also points out potential barriers that companies face to implement sustainability-related KM practices.     

Risk management in corporate planning

The risk distribution matrix (RDM) is to be applied in resource allocation and is a means of placing environmental risk in perspective. All forms of business operations should be included so that a company has a comprehensive picture of its commitments in safe, moderate, and high-risk countries. Corporate self-analysis is involved in the first three steps. The fourth step seeks to correct the risk profile through multiple strategies. Many years are likely to be required before a company achieves its desired profit/risk composition.

The advantage of the system is its individualization. Within the general framework given on the preceding pages, companies can make decisions based on factors unique to their industry, current position, preferred position and flexibility within the constraints identified. Ultimately, RDM provides a thorough evaluation system custom tailored to each company, insuring more profitable overseas transactions.     

11 Postcards from the Edge

Abstract

Environmental issues, while of growing interest, have been outside the main focus of business scholarship. This position on the periphery may have been a good thing. It allowed scholars of business and the environment to consider unusual theories and evaluate overlooked phenomenon. In doing so, they have created a body of research providing new insights into two topics of mainstream interest: (a) the sources of competitive advantage and (b) the origin and function of self-regulatory institutions.     

Slack free MEA and RDM with comprehensive efficiency measures

This paper extends two directional distance function models, the Multi-directional Efficiency Analysis (MEA) Model and the Range Directional Model (RDM), in order to account for any type of technical inefficiency, i.e. both directional and non-directional inefficiencies. We first focus on the variable returns to scale (VRS) case, because both VRS-MEA and RDM are translation invariant models, which mean that both models are able to deal with negative data. Our main result is the definition of a new comprehensive efficiency measure which is units invariant and translation invariant and covers both models. Secondly, we introduce the RDM model under constant returns to scale (CRS) together with a new comprehensive efficiency measure.     

Hostile media perceptions and consumption of genetically modified and organic foods: Examining the mediating role of risk-benefit assessments

Drawing upon the hostile media effect, this study examined how perceived media bias in covering genetically modified (GM) food influences individuals’ risk–benefit assessments of it and their food consumption behaviors. The results of a nationally representative survey (N = 1364) showed that individuals seeing media coverage as more biased in favor of GM food perceived it as more hazardous, which was related to a higher proportion of organic food consumption in their diets. In contrast, perceived media coverage as less slanted toward GM food was associated with more benefit perceptions of it, thereby predicting its higher proportion in individuals’ diets. More importantly, the indirect effect of perceived media bias on GM food consumption through benefit perceptions was more pronounced among males than females. The findings of this study not only provide empirical evidence of the perceptual and behavioral outcomes of hostile media perceptions, but also offer valuable insights for journalists and education practitioners to improve public understanding of emerging food technologies.